The 'Out-of-sample' Performance of Long-Run Risk Models

This paper studies the ability of long-run risk models, following Bansal and Yaron (2004) and others, to explain out-of-sample asset returns associated with the equity premium puzzle, size and book-to-market effects, momentum, reversals, and bond returns of different maturity and credit ratings. We examine stationary and cointegrated versions of the models using annual data for 1931-2006. We find that the models perform comparably overall to the simple CAPM. A cointegrated version of the model outperforms a stationary version. The long-run risk models perform relatively well on the momentum effect, and earnings momentum in particular. For some of the excess returns the long-run risk models deliver smaller average pricing errors than the CAPM, but they often have larger error variances, and the mean squared prediction errors are broadly similar